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Chest. 2004 Feb;125(2):704-11.

Grading airway stenosis down to the segmental level using virtual bronchoscopy.

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Institute of Diagnostic Radiology , Division of Pulmonology, Inselspital, University of Berne, Freiburgstrasse 20, 3010 Berne, Switzerland.



To assess the sensitivity of noninvasive virtual bronchoscopy based on multirow detector CT scanning in detecting and grading central and segmental airway stenosis using flexible bronchoscopic findings as the reference standard.


In a blinded controlled trial, multirow detector CT virtual bronchoscopy and flexible bronchoscopy were used to search for and grade airway stenosis in 20 patients. CT scan data were obtained with a multirow detector CT scanner using 4 x 1 mm collimation. Flexible bronchoscopy findings were graded by a pulmonologist and served as the reference standard for 176 central airway regions (ie, trachea, main bronchi, and lobar bronchi) and 302 segmental airway regions. The extent of airway narrowing was categorized as grade 0 (no narrowing), grade 1 (< 50%), or grade 2 (> or =50%).


Flexible bronchoscopy revealed 30 stenoses in the central airways and 10 in the segmental airways. Virtual bronchoscopy detected 32 stenoses in the central airways (sensitivity, 90.0%; specificity, 96.6%; accuracy, 95.5%) and 22 in the segmental airways (sensitivity, 90.0%; specificity, 95.6%; accuracy, 95.5%). The number of false-positive findings was higher in the segmental airways (13 false-positive findings) than in the central airways (5 false-positive findings), which caused a lower positive predictive value for the segmental airways (40.9%) than for the central airways (84.4%). Flexible and virtual bronchoscopic gradings correlated better for central airway stenosis (r = 0.87) than for segmental airway stenosis (r = 0.61).


Although a high sensitivity was found for the detection of both central and segmental airway stenosis, the number of false-positive findings was higher for segmental airways. However, noninvasive multirow detector CT virtual bronchoscopy enables high-resolution endoluminal imaging of the airways down to the segmental bronchi.

[Indexed for MEDLINE]

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